Some other things to think about regarding
this (to add what I said below): Bigger tracts will often have bigger masks,
and if you are really interested in structural asymmetries, you want to be sure
that you get the entire pathway for each of your subjects. If you leave
something out, you could either create a false asymmetry or miss a true one. Making
sure you get the whole pathway (but only the whole pathway), is more important
than keeping the size of your masks exactly the same in my opinion. At the
same time, if you are using the size of the ROI as a part of your thresholding
or normalization scheme, you need to be sure that you don’t have “extra” voxels
in your ROIs, i.e. voxels that don’t track the pathway, or don’t track anything
at all. Example: You have ROI A of 100 voxels in which 50 voxels track a
pathway of interest. You have ROI B of 50 voxels in which all 50 voxels track
the pathway of interest. If you are generating thresholds based on the size of
your ROIs, the pathway from ROI A will be more stringently thresholded than the
pathway from ROI B.
I personally tried both waytotal-based
thresholding and thresholding based on total number of samples (# voxels in the
ROI X # of samples sent out per voxel) on a study of pathway asymmetry. I
found significantly better correlation between a gold standard measure of
functional lateralization and tract volume asymmetries generated from thresholding
based on total number of samples than on tract volume asymmetries generated
from waytotal-based thresholding. I observed that waytotal-based thresholding
tended to make pathway volumes more consistent across subjects and hemispheres,
thus making it harder to see interhemispheric differences.
Regarding normalization vs thresholding,
you will have to do thresholding regardless of whether you normalize. If you
normalize, you can just use the same number as your threshold for all subjects,
but you lose information about the absolute pathway intensities. If you don’t
normalize, you will need to calculate the threshold separately for each pathway
(i.e. decide on some proportion of the waytotal or total number of samples
tracked, then for each pathway, multiply the proportion X the waytotal or the
total number of samples tracked to get the threshold value for that pathway). I
think this is more of a question of personal taste, rather than right or wrong,
as both methods are equally valid for interhemispheric comparisons. If you
want to compare across subjects, however, it is better to normalize (and to
normalize using wayotals), as this can account for global differences between
scans (e.g. more motion).
Peace,
Matt.
From:
Sent: Wednesday, March 25, 2009
9:28 AM
To: [log in to unmask]
Subject: [FSL] asymmetires
Hi,
We want to compare the structural asymmetries between the right
and left hemisphere by probabilistic tractography. We still
have some concerns: if the size of the masks will have an effect
on the results? For example, a big mask will have more tracts, and
in fact we couldn't make the masks exactly the same on the
both sides. The second, for comparing the results, if it
is necessary to do the normalization and what is the function
of normalization? In one of your
emails, it mentioned that:
My understanding is that
dividing by the waytotal is the way to normalize
across subjects as best as you can. Then
you could threshold at some
fractional proportion of the waytotal and
binarize. This should give you
the most similar spatial distributions
across subjects. However, I think
that this method is less useful when you are
making comparisons within a
brain, for example between the same pathway
in the two hemispheres, when you
are interested in pathway asymmetries for
example.
So what is the best
method, if we are interested in pathway asymmetries?
Best Regards,
Yan
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